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J 61 Feature G Rid C Omputing published presentations and documents on DocSlides.

Automation Fair 2016 Event Promotion

Automation Fair 2016 Event Promotion

  • lindy-dunigan
  • 12 Slides

New Products and Solutions Directory. New Product...

Feature Writing

Feature Writing

  • giovanna-bartolotta
  • 5 Slides

Features are not a first-hand account of the news...

Turning Down the Noise in the Blogosphere

Turning Down the Noise in the Blogosphere

  • ellena-manuel
  • 34 Slides

Khalid El-. Arini. , . Gaurav. Veda, . Dafna. ....

Lecture 5: Feature descriptors and matching

Lecture 5: Feature descriptors and matching

  • celsa-spraggs
  • 55 Slides

CS5670: Computer Vision. Noah Snavely. Reading. S...

Chasing the evolving web

Chasing the evolving web

  • tatiana-dople
  • 26 Slides

Aaron Powell, @. slace. Readify. Senior Develope...

Marketing 2.07

Marketing 2.07

  • natalia-silvester
  • 13 Slides

2.07B Analyze product information to identify pro...

1 The MMC is

1 The MMC is

  • danika-pritchard
  • 12 Slides

 68.2 mm, the largest allowable diameter for t...

Batch Normalization: Accelerating Deep Network Training by

Batch Normalization: Accelerating Deep Network Training by

  • min-jolicoeur
  • 18 Slides

CS838. . Motivation. Old school related concept:...

Efficient Logistic Regression with Stochastic Gradient Desc

Efficient Logistic Regression with Stochastic Gradient Desc

  • tatiana-dople
  • 34 Slides

William Cohen. 1. SGD for Logistic Regression. 2....

The Simple

The Simple

  • stefany-barnette
  • 14 Slides

Corpus. Tool. Martin Weisser. Research . Center. ...

Special Topic on Image Retrieval

Special Topic on Image Retrieval

  • karlyn-bohler
  • 71 Slides

2014-03. Popular Visual Features. Global feature....

Creating a Cutting-Edge Game for Windows Tablets

Creating a Cutting-Edge Game for Windows Tablets

  • giovanna-bartolotta
  • 84 Slides

Chas. Boyd. Windows . Graphics. 3-043. The Broad ...

Parametric Modeling

Parametric Modeling

  • kittie-lecroy
  • 40 Slides

3D Modeling Steps - Sketch. Step 1 . Sketch Geome...

Feature-Aligned T-Meshes

Feature-Aligned T-Meshes

  • trish-goza
  • 25 Slides

Ashish. Myles. †. Nico. . Pietroni. * . Denis...

SUPER: Towards Real-time Event Recognition in Internet Vide

SUPER: Towards Real-time Event Recognition in Internet Vide

  • alexa-scheidler
  • 16 Slides

Yu-Gang . Jiang. School of Computer Science. Fuda...

What does speech “look” like

What does speech “look” like

  • debby-jeon
  • 12 Slides

to an Automatic Speech Recognition System? . Jian...

BING: Binarized Normed Gradients for Objectness Estimation

BING: Binarized Normed Gradients for Objectness Estimation

  • alida-meadow
  • 31 Slides

Ming-Ming Cheng . . Ziming. Zhang . . Wen-Ya...

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  • celsa-spraggs
  • 27 Slides

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  • jane-oiler
  • 27 Slides

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Product X Release Y:

Product X Release Y:

  • lindy-dunigan
  • 52 Slides

Concept Commit V1. Josephine Soap. Freda Bloggs. ...

Face feature detection using Java and OpenCV

Face feature detection using Java and OpenCV

  • debby-jeon
  • 14 Slides

1. Content. What is . OpenCV. ?. What is face det...

Enabling the Cloud

Enabling the Cloud

  • pasty-toler
  • 17 Slides

AT&T. Margaret T. Chiosi. Executive Director ...

Turning Down the Noise in the Blogosphere

Turning Down the Noise in the Blogosphere

  • tatyana-admore
  • 33 Slides

Khalid El-. Arini. , . Gaurav. Veda, . Dafna. ....

INSTALLING RQDA

INSTALLING RQDA

  • calandra-battersby
  • 3 Slides

WINDOWS, MAC and LINUX. Resources. RQDA website: ...

Multi-Local Feature Manifolds for Object Detection

Multi-Local Feature Manifolds for Object Detection

  • min-jolicoeur
  • 30 Slides

Oscar . Danielsson. (osda02@csc.kth.se). Stefan ...

“Two Paws Up For Red Paw”

“Two Paws Up For Red Paw”

  • tatiana-dople
  • 11 Slides

Achieve 3000. October 3. rd. & 4. th. . Bec...

Answer Extraction

Answer Extraction

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Ling573. NLP Systems and Applications. May 16, 20...

Audio Feature Representations

Audio Feature Representations

  • giovanna-bartolotta
  • 1 Slides

Detecting Semantic Concepts In Consumer Videos Us...

Passive Thin Object Reconstruction from

Passive Thin Object Reconstruction from

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  • 43 Slides

Uncalibrated. Cameras. Erick Martin del Campo. P...

CHAPTER ONE – Part 2

CHAPTER ONE – Part 2

  • myesha-ticknor
  • 36 Slides

Geometrical Tolerances. 1. CHAPTER ONE. : . . ...

Cubical Marching Squares : Adaptive Feature Preserving Surf

Cubical Marching Squares : Adaptive Feature Preserving Surf

  • marina-yarberry
  • 52 Slides

EUROGRAPHICS 2005. Presenter : . Jong. -Hyun Kim....

reqT.org

reqT.org

  • tawny-fly
  • 17 Slides

. Towards . a Semi-Formal, Open and . Scalable ....

Image Feature Descriptors

Image Feature Descriptors

  • myesha-ticknor
  • 41 Slides

Kenton McHenry, Ph.D.. Research Scientist. Raster...

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

  • alexa-scheidler
  • 76 Slides

Lucy . Kuncheva. School of Computer Science. Bang...

Passive Thin Object Reconstruction from

Passive Thin Object Reconstruction from

  • kittie-lecroy
  • 0 Slides

Uncalibrated. Cameras. Erick Martin del Campo. P...

Retrieving Sounds by Vocal Imitation Recognition

Retrieving Sounds by Vocal Imitation Recognition

  • giovanna-bartolotta
  • 0 Slides

Yichi Zhang & Zhiyao Duan. Poster for MLSP 20...

Einführung in die Programmierung

Einführung in die Programmierung

  • myesha-ticknor
  • 0 Slides

Introduction to Programming. Prof. Dr. Bertrand M...

Finite Mixture Models and EM Algorithm

Finite Mixture Models and EM Algorithm

  • liane-varnes
  • 0 Slides

McLachlan, G., & Peel, D. (2001). . Finite m...

Build your own Habitat T

Build your own Habitat T

  • debby-jeon
  • 0 Slides

he story of my Helix implementations. Presentatio...

Introduction to Structured Prediction and Domain Adaptation

Introduction to Structured Prediction and Domain Adaptation

  • calandra-battersby
  • 0 Slides

Alexander Fraser. CIS, LMU Munich. 2017-10-24 ....

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